A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics
Summary: Model-based analysis compares GPUs and CPUs for database analytics and introduces Crystal, a GPU library of parallel primitives for near-materialization SQL. Selections, projections, and sorts approach the bandwidth gain, joins lag, yet full queries exceed the ratio (~25x) on benchmarks due to CPU vectorization limits. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Anil Shanbhag (Massachusetts Institute of Technology)
- 2. Samuel Madden (Massachusetts Institute of Technology)
- 3. Xiangyao Yu (University of Wisconsin)
BibTeX Citation
@inproceedings{shanbhag_sigmod20,
title = {{A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics}},
author = {Shanbhag, Anil and Madden, Samuel and Yu, Xiangyao},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3380595},
url = {https://dl.acm.org/doi/10.1145/3318464.3380595},
year = {2020}
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